Targeted isolation and AI-based analysis of edible fungal polysaccharides: Emphasizing tumor immunological mechanisms and future prospects as mycomedicines

Abstract

Edible fungal polysaccharides have emerged as significant bioactive compounds with diverse therapeutic potentials, including notable anti-tumor effects. Derived from various fungal sources, these polysaccharides exhibit complex biological activities such as antioxidant, immune-modulatory, anti-inflammatory, and anti-obesity properties. In cancer therapy, members of this family show promise in inhibiting tumor growth and metastasis through mechanisms like apoptosis induction and modulation of the immune system. This review provides a detailed examination of contemporary techniques for the targeted isolation and structural elucidation of edible fungal polysaccharides. Additionally, the review highlights the application of advanced artificial intelligence (AI) methodologies to facilitate efficient and accurate structural analysis of these polysaccharides. It also explores their interactions with immune cells within the tumor microenvironment and their role in modulating gut microbiota, which can enhance overall immune function and potentially reduce cancer risks. Clinical studies further demonstrate their efficacy in various cancer treatments. Overall, edible fungal polysaccharides represent a promising frontier in cancer therapy, leveraging their natural origins and minimal toxicity to offer novel strategies for comprehensive cancer management.

Keywords: Deep learning; Edible fungal polysaccharide; Glycan structure prediction”; Gut microbiota; Mycomedicines; Structural characterization; Tumor microenvironment.